Fatna Belqasmi
Papers
7
Total Citations
78
H-Index
6
About
Fatna Belqasmi is a researcher whose work sits at the intersection of next-generation networking, cloud computing, and intelligent healthcare technologies. She has made significant contributions to the emerging field of Tactile Internet, with a particular focus on remote robotic surgery — one of the most demanding 5G applications, requiring ultra-low latency of just 1 ms and reliability of 99.999%. Her most cited work (27 citations) proposes a machine learning framework to handle delayed and lost packets in surgical teleoperation, directly addressing one of the field's most critical safety challenges. Belqasmi has also been a pioneer in cloud and fog-based architectures for robotic applications, exploring how cloud computing paradigms can reduce costs and improve resource efficiency in robotics deployment across healthcare, disaster management, and manufacturing. Her 2019 work on fog-based remote phobia treatment (13 citations) highlights her interest in applying haptic and Tactile Internet technologies to mental health care. More recently, she has tackled complex resource allocation problems through joint placement and scheduling of virtual network function graphs for surgical systems. Across her career, Belqasmi's research consistently bridges theoretical networking innovation with life-critical real-world applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2An infrastructure for robotic applications as cloud computing services17 citations · 2014
- 3A Fog-Based Architecture for Remote Phobia Treatment13 citations · 2019
- 4Remote Robotic Surgery: Joint Placement and Scheduling of VNF-FGs6 citations · 2022
- 5
- 6
- 7Towards cloud-based architectures for robotic applications provisioning3 citations · 2013